Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 688 327 694 924 891 124 476 603 955 461 818 634 798 612 909 370 772 997 837 34
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 891 997 NA 476 837 NA 909 370 34 327 603 NA 612 124 955 461 688 818 924 634 694 772 798
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 2 1 1 4 3 2 3 2 4 3
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "b" "i" "h" "t" "s" "X" "U" "S" "Q" "T"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 4 9 15 18
which( manyNumbersWithNA > 900 )
[1] 2 7 15 19
which( is.na( manyNumbersWithNA ) )
[1] 3 6 12
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 924 955 909 997
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 924 955 909 997
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 924 955 909 997
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "X" "U" "S" "Q" "T"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "b" "i" "h" "t" "s"
manyNumbers %in% 300:600
[1] FALSE TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE
[19] FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 2 7 10 16
sum( manyNumbers %in% 300:600 )
[1] 4
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" "large" NA "small" "large" NA "large" "small" "small" "small" "large" NA "large" "small"
[15] "large" "small" "large" "large" "large" "large" "large" "large" "large"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "large" "UNKNOWN" "small" "large" "UNKNOWN" "large" "small" "small" "small" "large"
[12] "UNKNOWN" "large" "small" "large" "small" "large" "large" "large" "large" "large" "large"
[23] "large"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 891 997 NA 0 837 NA 909 0 0 0 603 NA 612 0 955 0 688 818 924 634 694 772 798
unique( duplicatedNumbers )
[1] 2 1 4 3
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 2 1 4 3
duplicated( duplicatedNumbers )
[1] FALSE FALSE TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 2
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 997
which.min( manyNumbersWithNA )
[1] 9
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 34
range( manyNumbersWithNA, na.rm = TRUE )
[1] 34 997
manyNumbersWithNA
[1] 891 997 NA 476 837 NA 909 370 34 327 603 NA 612 124 955 461 688 818 924 634 694 772 798
sort( manyNumbersWithNA )
[1] 34 124 327 370 461 476 603 612 634 688 694 772 798 818 837 891 909 924 955 997
sort( manyNumbersWithNA, na.last = TRUE )
[1] 34 124 327 370 461 476 603 612 634 688 694 772 798 818 837 891 909 924 955 997 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 997 955 924 909 891 837 818 798 772 694 688 634 612 603 476 461 370 327 124 34 NA NA NA
manyNumbersWithNA[1:5]
[1] 891 997 NA 476 837
order( manyNumbersWithNA[1:5] )
[1] 4 5 1 2 3
rank( manyNumbersWithNA[1:5] )
[1] 3 4 5 1 2
sort( mixedLetters )
[1] "b" "h" "i" "Q" "s" "S" "t" "T" "U" "X"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 9.5 7.0 4.5 7.0 7.0 3.0 1.5 4.5 9.5 1.5
rank( manyDuplicates, ties.method = "min" )
[1] 9 6 4 6 6 3 1 4 9 1
rank( manyDuplicates, ties.method = "random" )
[1] 9 6 5 8 7 3 1 4 10 2
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 0.63861919 1.22429175 0.87107370 -0.43413212
[10] -0.20475502 -1.82245532 -1.76090481 0.39435939 1.47180143 -0.04250894
round( v, 0 )
[1] -1 0 0 0 1 1 1 1 0 0 -2 -2 0 1 0
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.6 1.2 0.9 -0.4 -0.2 -1.8 -1.8 0.4 1.5 0.0
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.64 1.22 0.87 -0.43 -0.20 -1.82 -1.76 0.39 1.47 -0.04
floor( v )
[1] -1 -1 0 0 1 0 1 0 -1 -1 -2 -2 0 1 -1
ceiling( v )
[1] -1 0 0 1 1 1 2 1 0 0 -1 -1 1 2 0
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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